Data Quality Assessment Report
massqc from tidymass by Xiaotao Shen
2022-03-06
PARAMETERS
Table 1: Parameter setting
| pacakge_name | function_name | parameter | time |
|---|---|---|---|
| massprocesser | process_data | path:~/scratch60 | 2022-02-28 13:05:44 |
| massprocesser | process_data | polarity:negative | 2022-02-28 13:05:44 |
| massprocesser | process_data | ppm:20 | 2022-02-28 13:05:44 |
| massprocesser | process_data | peakwidth:5,30 | 2022-02-28 13:05:44 |
| massprocesser | process_data | snthresh:10 | 2022-02-28 13:05:44 |
| massprocesser | process_data | prefilter:3,500 | 2022-02-28 13:05:44 |
| massprocesser | process_data | fitgauss:FALSE | 2022-02-28 13:05:44 |
| massprocesser | process_data | integrate:2 | 2022-02-28 13:05:44 |
| massprocesser | process_data | mzdiff:0.01 | 2022-02-28 13:05:44 |
| massprocesser | process_data | noise:500 | 2022-02-28 13:05:44 |
| massprocesser | process_data | threads:6 | 2022-02-28 13:05:44 |
| massprocesser | process_data | binSize:0.025 | 2022-02-28 13:05:44 |
| massprocesser | process_data | bw:5 | 2022-02-28 13:05:44 |
| massprocesser | process_data | output_tic:FALSE | 2022-02-28 13:05:44 |
| massprocesser | process_data | output_bpc:FALSE | 2022-02-28 13:05:44 |
| massprocesser | process_data | output_rt_correction_plot:FALSE | 2022-02-28 13:05:44 |
| massprocesser | process_data | min_fraction:0.5 | 2022-02-28 13:05:44 |
| massprocesser | process_data | fill_peaks:FALSE | 2022-02-28 13:05:44 |
| massdataset | create_mass_dataset() | no:no | 2022-02-28 14:07:06 |
| massdataset | mutate() | parameter_1:batch=as.character(batch) | 2022-03-05 16:53:35 |
| massdataset | mutate_variable_na_freq() | according_to_samples:QC01,QC02,QC03,QC04,QC05,… | 2022-03-05 17:08:15 |
| massdataset | mutate_variable_na_freq() | according_to_samples:men_normal_166,men_normal_2332,men_normal_2357,men_normal_2371,men_normal_2407,… | 2022-03-05 17:08:15 |
| massdataset | mutate_variable_na_freq() | according_to_samples:menLCCstage1_1122,menLCCstage1_1487,menLCCstage1_1532,menLCCstage1_1941,menLCCstage1_1969,… | 2022-03-05 17:08:15 |
| massdataset | filter() | parameter:~na_freq < 0.2 & (na_freq.1 < 0.5 | na_freq.2 < 0.5) |
2022-03-05 17:08:20 |
| massdataset | mutate() | parameter_1:class=case_when(class == “QC” ~ class, TRUE ~ “Subject”) | 2022-03-05 17:19:31 |
| masscleaner | impute_mv() | method:knn | 2022-03-05 17:46:54 |
| masscleaner | impute_mv() | rowmax:0.5 | 2022-03-05 17:46:54 |
| masscleaner | impute_mv() | colmax:0.8 | 2022-03-05 17:46:54 |
| masscleaner | impute_mv() | maxp:1500 | 2022-03-05 17:46:54 |
| masscleaner | impute_mv() | rng.seed:362436069 | 2022-03-05 17:46:54 |
| masscleaner | impute_mv() | sample_id:menLCCstage1_1122,menLCCstage1_1487,menLCCstage1_1532,menLCCstage1_1941,menLCCstage1_1969,… | 2022-03-05 17:46:54 |
| masscleaner | normalize_data() | method:svr | 2022-03-05 21:06:01 |
| masscleaner | normalize_data() | keep_scale:TRUE | 2022-03-05 21:06:01 |
| masscleaner | normalize_data() | multiple:1 | 2022-03-05 21:06:01 |
| masscleaner | normalize_data() | threads:4 | 2022-03-05 21:06:01 |
SAMPLE INFORMATION
#> --------------------
#> massdataset version: 0.99.4
#> --------------------
#> 1.expression_data:[ 3808 x 299 data.frame]
#> 2.sample_info:[ 299 x 6 data.frame]
#> 3.variable_info:[ 3808 x 6 data.frame]
#> 4.sample_info_note:[ 6 x 2 data.frame]
#> 5.variable_info_note:[ 6 x 2 data.frame]
#> 6.ms2_data:[ 0 variables x 0 MS2 spectra]
#> --------------------
#> Processing information (extract_process_info())
#> create_mass_dataset ----------
#> Package Function.used Time
#> 1 massdataset create_mass_dataset() 2022-02-28 14:07:06
#> process_data ----------
#> Package Function.used Time
#> 1 massprocesser process_data 2022-02-28 13:05:44
#> mutate ----------
#> Package Function.used Time
#> 1 massdataset mutate() 2022-03-05 16:53:35
#> 2 massdataset mutate() 2022-03-05 17:19:31
#> mutate_variable_na_freq ----------
#> Package Function.used Time
#> 1 massdataset mutate_variable_na_freq() 2022-03-05 17:08:15
#> 2 massdataset mutate_variable_na_freq() 2022-03-05 17:08:15
#> 3 massdataset mutate_variable_na_freq() 2022-03-05 17:08:15
#> filter ----------
#> Package Function.used Time
#> 1 massdataset filter() 2022-03-05 17:08:20
#> impute_mv ----------
#> Package Function.used Time
#> 1 masscleaner impute_mv() 2022-03-05 17:46:54
#> normalize_data ----------
#> Package Function.used Time
#> 1 masscleaner normalize_data() 2022-03-05 21:06:01
Figure 1: Peak intensity profile.
MISSING VALUES
MISSING VALUES IN DATASET
Black is MV.
Figure 2: Missing values in dataset
MISSING VALUES IN VARIABLES
Figure 3: Missing values in variables
MISSING VALUES IN SAMPLES
Figure 4: Missing values in samples
RSD DISTRIBUTATION
Figure 5: RSD distributation
INTENSITY FOR ALL THE VARIABLES
Figure 6: Intensity for all the variables
SAMPLE CORRELATION
Figure 7: Sample correlation
PCA score plot
